Online optimal power flow with renewables

Seung Jun Kim, Geogios B. Giannakis, Kwang Y. Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Optimal power flow (OPF) is a critical control task for reliable and efficient operation of power grids. Significant challenges are anticipated in the development of future power systems, as a substantial amount of inherently uncertain renewable resources are incorporated, imposing volatile dynamics to the grid. In this work, an online learning approach, which does not require elaborate models for uncertainty, yet is capable of providing a provable performance guarantee, is adopted to tackle the OPF with renewables in an online fashion. A two-stage procedure is considered, where the conventional generation level is committed before the renewable output is revealed, followed by spot market transactions to account for imbalance. Simulated tests with a 30-bus case show that, under high variability of renewables, the proposed hedging scheme beats a static alternative, which solves two OPF problems per time slot.

Original languageEnglish (US)
Title of host publicationConference Record of the 48th Asilomar Conference on Signals, Systems and Computers
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages355-360
Number of pages6
ISBN (Electronic)9781479982974
DOIs
StatePublished - Apr 24 2015
Event48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 2 2014Nov 5 2014

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2015-April
ISSN (Print)1058-6393

Other

Other48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/2/1411/5/14

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